Abstract:

Beset by energy shortage and environmental pollution with the sharp rise in car ownership, electric vehicles (EVs) are currently receiving high praise from people. However, the energy used in EVs must be supplied by hundreds of cells when they are driven for a limited energy density of the lithium ion; as a result, the battery management system (BMS) can be viewed as the core technology for EVs. Unluckily, some parameters cannot be measured directly and are obtained only through model estimation. The appropriate model of a lithium-ion battery is the key to the efficiency, precision, and stability of the BMS. Several factors, including material, ambient temperature, work mode, and aging degree, are well known to be closely related to the lithium-ion battery model; nevertheless, having such elements during modeling is difficult. This study introduces the function and structure of the BMS, enabling the listing of concerned references regarding the battery model in the recent years. Three sorts of model (i.e., electrical characteristic, thermal, and electric-thermal coupling models) are then discussed separately. Although the first and second models can clearly reveal the work mechanism of the lithium-ion battery, the large amount of calculation makes it hard to be accepted in engineering considering the current situation. Adversely, the third model combines the advantages of the two models and is widely used for its relative simplicity. Herein, the applications of such models on internal states, such as state of charge (SOC), state of health (SOH), and inner temperature of battery, are described based on a correlative discussion. The SOC variable of EV is as significant as the oil gauge of the internal combustion engine vehicle; thus, it is relatively mature. The SOH is influenced by the current, temperature, and SOC and is very relevant to mechanical vibration and overpotential. Meanwhile, the internal temperature is vital to the capacity, discharging efficiency, span life, and safety of the lithium-ion battery; therefor, how to maintain the proper temperature is very crucial. Considering the coupling of estimation variables (e.g., SOC and inner temperature variable), the estimation accuracy should be greatly enhanced to ensure the BMS reliability. In the future, the lithium-ion battery model is expected to be simplified continually, thereby enabling the invariable satisfaction of a real-time BMS.

Key words: lithium battery, battery management system, modeling method